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End of training

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  1. .gitattributes +4 -0
  2. README.md +84 -0
  3. checkpoint-1200/optimizer.bin +3 -0
  4. checkpoint-1200/pytorch_lora_weights.safetensors +3 -0
  5. checkpoint-1200/random_states_0.pkl +3 -0
  6. checkpoint-1200/scheduler.bin +3 -0
  7. checkpoint-1600/optimizer.bin +3 -0
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  15. checkpoint-2400/optimizer.bin +3 -0
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  23. checkpoint-3200/optimizer.bin +3 -0
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  29. checkpoint-3600/random_states_0.pkl +3 -0
  30. checkpoint-3600/scheduler.bin +3 -0
  31. checkpoint-400/optimizer.bin +3 -0
  32. checkpoint-400/pytorch_lora_weights.safetensors +3 -0
  33. checkpoint-400/random_states_0.pkl +3 -0
  34. checkpoint-400/scheduler.bin +3 -0
  35. checkpoint-4000/optimizer.bin +3 -0
  36. checkpoint-4000/pytorch_lora_weights.safetensors +3 -0
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  39. checkpoint-800/optimizer.bin +3 -0
  40. checkpoint-800/pytorch_lora_weights.safetensors +3 -0
  41. checkpoint-800/random_states_0.pkl +3 -0
  42. checkpoint-800/scheduler.bin +3 -0
  43. image_0.png +3 -0
  44. image_1.png +3 -0
  45. image_2.png +3 -0
  46. image_3.png +3 -0
  47. pytorch_lora_weights.safetensors +3 -0
.gitattributes CHANGED
@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ image_0.png filter=lfs diff=lfs merge=lfs -text
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+ image_1.png filter=lfs diff=lfs merge=lfs -text
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+ image_2.png filter=lfs diff=lfs merge=lfs -text
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+ image_3.png filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ base_model: black-forest-labs/FLUX.1-Fill-dev
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+ library_name: diffusers
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+ license: other
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+ instance_prompt: A TOK railroad-gap
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+ widget:
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+ - text: A TOK railroad-gap
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+ output:
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+ url: image_0.png
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+ - text: A TOK railroad-gap
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+ output:
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+ url: image_1.png
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+ - text: A TOK railroad-gap
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+ output:
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+ url: image_2.png
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+ - text: A TOK railroad-gap
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+ output:
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+ url: image_3.png
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+ tags:
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+ - text-to-image
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+ - diffusers-training
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+ - diffusers
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+ - lora
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+ - flux
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+ - flux-diffusers
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+ - template:sd-lora
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the training script had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+
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+ # Flux-Fill DreamBooth LoRA - bobby97/flux-fill-railroad-3-lora
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+
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+ <Gallery />
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+
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+ ## Model description
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+
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+ These are bobby97/flux-fill-railroad-3-lora DreamBooth LoRA weights for black-forest-labs/FLUX.1-Fill-dev.
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+
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+ The weights were trained using [DreamBooth](https://dreambooth.github.io/) with a custom [Flux diffusers trainer](https://github.com/Sebastian-Zok/FLUX-Fill-LoRa-Training).
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+
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+ Was LoRA for the text encoder enabled? False.
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+
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+ ## Trigger words
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+
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+ You should use `A TOK railroad-gap` to trigger the image generation.
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+
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+ ## Download model
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+
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+ [Download the *.safetensors LoRA](bobby97/flux-fill-railroad-3-lora/tree/main) in the Files & versions tab.
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+
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+ ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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+
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+ ```py
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+ from diffusers import AutoPipelineForText2Image
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+ import torch
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+ pipeline = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to('cuda')
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+ pipeline.load_lora_weights('bobby97/flux-fill-railroad-3-lora', weight_name='pytorch_lora_weights.safetensors')
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+ image = pipeline('A TOK railroad-gap').images[0]
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+ ```
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+
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+ For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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+
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+ ## License
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+
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+ Please adhere to the licensing terms as described [here](https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md).
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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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+ ```python
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+ # TODO: add an example code snippet for running this diffusion pipeline
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+ ```
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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
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